• Journal of Power Electronics
• /
• v.12 no.6
• /
• pp.904-911
• /
• 2012

This paper presents a fuzzy adaptive speed controller that guarantees a fast dynamic behavior and a precise trajectory tracking capability for surfaced-mounted permanent magnet synchronous motors (SPMSMs). The proposed fuzzy adaptive control strategy is simple and easy to implement. In addition, the proposed speed controller is very robust to system parameter and load torque variations because it does not require any accurate parameter values. The global stability of the proposed control system is analytically verified. To evaluate the proposed fuzzy adaptive speed controller, both simulation and experimental results are shown under motor parameter and load torque variations on a prototype SPMSM drive system.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.2
• /
• pp.117-123
• /
• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.921-923
• /
• 1999

In adaptive fuzzy control, fuzzy systems are used to approximate the unknown plant nonlinearities. However, because of the approximating error introduced into the feedback loop, it is difficult to guarantee the stability of the adaptive control algorithm. This paper presents a robust control algorithm against the reconstruction error and uniform boundedness of the all signals is estabilished in the Lyapunov sense.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.9
• /
• pp.106-121
• /
• 1993

A New fuzzy adaptive controller which is able to solve the problems of classical adaptive controllers and conventional fuzzy adaptive controllers is suggested in this paper. The architecture of a fuzzy adaptive controller using the robust property of a fuzzy controller is explained. A design procedure which can be carried out mathematically and systematically from the model of an objective system is suggested, and related mathematical theorems and their proofs are also given. The performance of the proposed adaptive control algorithm is analyzed through a design example and a DC motor control simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.5
• /
• pp.407-414
• /
• 2001

In this paper, we present a decentralized robust adaptive fuzzy controller for the transient stability and voltage regulation of a multimachine power system under a sudden fault. Power systems have uncertain dynamics due to various effects such a lightning, severe storms and equipment failure in addition to interconnections between generators. Hence a robust controller to deal with these uncertainties in needed. The fuzzy systems are adapted using a Lyapunov-based design and the stability of each closed-loop system is guaranteed. Simulation results show that satisfactory performance is achieved by proposed controller.

• Journal of Mechanical Science and Technology
• /
• v.18 no.4
• /
• pp.535-549
• /
• 2004

This paper proposes a sliding mode controller with fuzzy adaptive perturbation compensator(FAPC) to get a good control performance and reduce the chatter, The proposed algorithm can reduce the chattering because the proposed fuzzy adaptive perturbation compensator compensates the perturbation terms. The compensator computes the control input for compensating unmodeled dynamic terms and disturbance by using the observer-based fuzzy adaptive network(FAN) The weighting parameters of the compensate. are updated by on-line adaptive scheme in order to minimize the estimation error and the estimation velocity error of each actuator. Therefore, the combination of sliding mode control and fuzzy adaptive network gives the robust and intelligent routine to get a good control performance. To evaluate the control performance of the proposed approach, tracking control is experimentally carried out for the hydraulic motion platform which consists of a 6-DOF parallel manipulator.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.50 no.1
• /
• pp.14-21
• /
• 2001

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. In indirect adaptive fuzzy control, based on the proved approximation capability of fuzzy systems, they are used to capture the unknown nonlinearities of the plant. Until now, most of the papers in the field of controller design for nonlinear system considers the affine system using fuzzy systems which have fixed grid-rule structure. We proposes a dynamic fuzzy rule insertion scheme where fuzzy rule-base grows as time goes on. With this method, the dynamic order of the controller reduces dramatically and an appropriate number of fuzzy rules are found on-line. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed-loop system is guaranteed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.26-30
• /
• 1995

In this study, the fuzzy approximator and sliding mode control (SMC) scheme are considered. An adaptive sliding mode control is proposed based on the SMC theory. This proposed control scheme is that a adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the sliding mode controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, an adaptive law is also intoduced and the stability of proposed control scheme are proven with simple adaptive law and roburst adaptive law. This proposed control scheme is applied to a single link robot arm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.4
• /
• pp.297-305
• /
• 1996

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.164-167
• /
• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.